This package provides a dataset about movies. This was previously contained in ggplot2, but has been moved its own package to reduce the download size of ggplot2.

Second-order summary statistics K- and pair-correlation functions describe interactions in point pattern data. This package provides computations to estimate those statistics on inhomogeneous point processes, using the methods of in T Shaw, J Møller, R Waagepetersen, 2020 <doi:10.48550/arXiv.2004.00527>.

Identifies implausible anthropometric (e.g., height, weight) measurements in irregularly spaced longitudinal datasets, such as those from electronic health records.

This package provides plotting functions for visualizing pedigrees and family trees. The package complements a behavior genetics package BGmisc [Garrison et al. (2024) <doi:10.21105/joss.06203>] by rendering pedigrees using the ggplot2 framework. Features include support for duplicated individuals, complex mating structures, integration with simulated pedigrees, and layout customization. Due to the impending deprecation of kinship2, version 1.0 incorporates the layout helper functions from kinship2. The pedigree alignment algorithms are adapted from kinship2 [Sinnwell et al. (2014) <doi:10.1159/000363105>]. We gratefully acknowledge the original authors: Jason Sinnwell, Terry Therneau, Daniel Schaid, and Elizabeth Atkinson for their foundational work.

Gradient-Enhanced Kriging as an emulator for computer experiments based on Maximum-Likelihood estimation.

Helper to add insets based on geom_sf() from ggplot2'. This package gives you a drop-in replacement for geom_sf() that supports adding a zoomed inset map without having to create and embed a separate plot.

Data sets used in the book Marra and Radice (2025, ISBN:9781032973111) "Copula Additive Distributional Regression Using R", for illustrating the fitting of various joint (and univariate) regression models, with several types of covariate effects, in the presence of equations errors association.

Supplies a set of functions to interface with bikeshare data following the General Bikeshare Feed Specification, allowing users to query and accumulate tidy datasets for specified cities/bikeshare programs.

Real-time quantitative polymerase chain reaction (qPCR) data by Guescini et al. (2008) <doi:10.1186/1471-2105-9-326> in tidy format. This package provides two data sets where the amplification efficiency has been modulated: either by changing the amplification mix concentration, or by increasing the concentration of IgG, a PCR inhibitor. Original raw data files: <https://static-content.springer.com/esm/art%3A10.1186%2F1471-2105-9-326/MediaObjects/12859_2008_2311_MOESM1_ESM.xls> and <https://static-content.springer.com/esm/art%3A10.1186%2F1471-2105-9-326/MediaObjects/12859_2008_2311_MOESM5_ESM.xls>.

This package provides functions for implementing the Generalized Bayesian Optimal Phase II (G-BOP2) design using various Particle Swarm Optimization (PSO) algorithms, including: - PSO-Default, based on Kennedy and Eberhart (1995) <doi:10.1109/ICNN.1995.488968>, "Particle Swarm Optimization"; - PSO-Quantum, based on Sun, Xu, and Feng (2004) <doi:10.1109/ICCIS.2004.1460396>, "A Global Search Strategy of Quantum-Behaved Particle Swarm Optimization"; - PSO-Dexp, based on Stehlà k et al. (2024) <doi:10.1016/j.asoc.2024.111913>, "A Double Exponential Particle Swarm Optimization with Non-Uniform Variates as Stochastic Tuning and Guaranteed Convergence to a Global Optimum with Sample Applications to Finding Optimal Exact Designs in Biostatistics"; - and PSO-GO.

This package provides a gate-keeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Computations related to group sequential primary and secondary boundaries. Refined secondary boundaries are calculated for a gate-keeping test on a primary and a secondary endpoint in a group sequential design with multiple interim looks. The choices include both the standard boundaries and the boundaries using error spending functions. See Tamhane et al. (2018), "A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks", Biometrics, 74(1), 40-48.

Genomic biology is not limited to the confines of the canonical B-forming DNA duplex, but includes over ten different types of other secondary structures that are collectively termed non-B DNA structures. Of these non-B DNA structures, the G-quadruplexes are highly stable four-stranded structures that are recognized by distinct subsets of nuclear factors. This package provide functions for predicting intramolecular G quadruplexes. In addition, functions for predicting other intramolecular nonB DNA structures are included.

Reads data collected from wearable acceleratometers as used in sleep and physical activity research. Currently supports file formats: binary data from GENEActiv <https://activinsights.com/>, .bin-format from GENEA devices (not for sale), and .cwa-format from Axivity <https://axivity.com>. Further, it has functions for reading text files with epoch level aggregates from Actical', Fitbit', Actiwatch', ActiGraph', and PhilipsHealthBand'. Primarily designed to complement R package GGIR <https://CRAN.R-project.org/package=GGIR>.

Utilizing Generative Artificial Intelligence models like GPT-4 and Gemini Pro as coding and writing assistants for R users. Through these models, GenAI offers a variety of functions, encompassing text generation, code optimization, natural language processing, chat, and image interpretation. The goal is to aid R users in streamlining laborious coding and language processing tasks.

Simulation tool to facilitate determination of required sample size to achieve category saturation for studies using multiple repertory grids in conjunction with content analysis.

This package provides additional display mediums for time series visualisations.

This package provides a ggplot2 extension that allows text to follow curved paths. Curved text makes it easier to directly label paths or neatly annotate in polar co-ordinates.

Enables calculation of image textures (Haralick 1973) <doi:10.1109/TSMC.1973.4309314> from grey-level co-occurrence matrices (GLCMs). Supports processing images that cannot fit in memory.

The correlations and linkage disequilibrium between tests can vary as a function of minor allele frequency thresholds used to filter variants, and also varies with different choices of test statistic for region-based tests. Appropriate genome-wide significance thresholds can be estimated empirically through permutation on only a small proportion of the whole genome.

This package provides a Gaussian or Student's t copula-based procedure for generating samples from discrete random variables with prescribed correlation matrix and marginal distributions.

Testing, Implementation and Forecasting of Grey Model (GM(1, 1)). For method details see Hsu, L. and Wang, C. (2007). <doi:10.1016/j.techfore.2006.02.005>.

Simulating, visualizing and comparing tumor clonal data by using simple commands. This aims at providing a tool to help researchers to easily simulate tumor data and analyze the results of their approaches for studying the composition and the evolutionary history of tumors.

Includes the ga.lts() function that estimates LTS (Least Trimmed Squares) parameters using genetic algorithms and C-steps. ga.lts() constructs a genetic algorithm to form a basic subset and iterates C-steps as defined in Rousseeuw and van-Driessen (2006) to calculate the cost value of the LTS criterion. OLS (Ordinary Least Squares) regression is known to be sensitive to outliers. A single outlying observation can change the values of estimated parameters. LTS is a resistant estimator even the number of outliers is up to half of the data. This package is for estimating the LTS parameters with lower bias and variance in a reasonable time. Version >=1.3 includes the function medmad for fast outlier detection in linear regression.

This package provides a simple API for downloading and reading xml data directly from Lattes <http://lattes.cnpq.br/>.